Today, the effective processing of the obtained data is the fundamental AREA of Big Data. Proficiency in this AREA allows for the significant reduction of the time spent on taking business decisions, and also it enables faster drawing of conclusions based on voluminous historical data.
While analysing a recently implemented project for a customer from the pharmaceutical sector, owing to which the time of processing data was significantly reduced by means of the Hadoop ecosystem, Apollogic experts decided that the currently available range of Big Data methods and tools guarantees even better improvement of data management and processing in a company.
The first objective of the new project was to create an application in the Scala language which uses received data and obtains the results faster than ever before. An additional step was testing the Apache Spark technology which uses the resources of RAM for computational purposes. Thus, Big Data Apollogic specialists wanted to prove that the correct implementation of the above tool may boost the process of data processing even several times compared to the Apache Hive solution which was originally used. Due to the limited availability of hardware resources, analogous data samples were prepared for testing purposes with the size of 15 GB each.